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Record W4388624661 · doi:10.1029/2023jc019864

Increased DIN Storage and ΔDIC/ΔDIN Ratio in the Subsurface Water of the Canada Basin, 1990‒2015

2023· article· en· W4388624661 on OpenAlexaboutno aff
Tianzhen Zhang, Qiang Hao, Haiyan Jin, Youcheng Bai, Yanpei Zhuang, Di Qi, Jianfang Chen

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsSubsurface flowBiogeochemical cycleStructural basinSink (geography)Environmental scienceOceanographyArcticGeologyHydrology (agriculture)InflowGroundwaterGeomorphologyEnvironmental chemistryGeography

Abstract

fetched live from OpenAlex

Abstract The subsurface layer of the Canada Basin contains large reservoirs of dissolved inorganic nitrogen and carbon (DIN and DIC, respectively). Under rapid change of Arctic climate system, these reservoirs may not only serve as potential material bases for primary production, but also for carbon source and sink. However, the long‐term trends in reservoirs and the interaction between reservoirs and the upper ocean are not fully understood. This study used two data sets to evaluate the long‐term trends in the DIN and DIC reservoirs in the subsurface layer of the Canada Basin during 1990–2015. The results indicate an increase of ∼35% in the subsurface DIN reservoir over 25 years, whereas the DIN concentration remained fairly constant. The discrepancy between the DIN reservoir and DIN concentration was primarily owing to the expansion of the subsurface layer, which increased the DIN stock but maintained a relatively stable DIN concentration. Additionally, the ΔDIC/ΔDIN ratio in the subsurface layer increased by ∼33% over 25 years, primarily due to denitrification on the pathway of Pacific inflow, such as Chukchi shelf. In the Canada Basin, the enhanced mixing between the subsurface and surface layers may promote primary production and render the subsurface layer a carbon source. Consequently, when studying the biogeochemical cycles in the changing Arctic Ocean, the long‐term interactions between the subsurface and surface layers in the Canada Basin should be further considered.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.267
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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